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相关论文: Procedural Music Generation Systems in Games

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Procedural Content Generation (PCG) is defined as the automatic creation of game content using algorithms. PCG has a long history in both the game industry and the academic world. It can increase player engagement and ease the work of game…

人工智能 · 计算机科学 2025-02-06 Mahdi Farrokhi Maleki , Richard Zhao

Procedural Content Generation (PCG) refers to the practice, in videogames and other games, of generating content such as levels, quests, or characters algorithmically. Motivated by the need to make games replayable, as well as to reduce…

人工智能 · 计算机科学 2020-03-18 Sebastian Risi , Julian Togelius

This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content. As the importance of PCG for game development increases,…

Procedural content generation (PCG) is a growing field, with numerous applications in the video game industry and great potential to help create better games at a fraction of the cost of manual creation. However, much of the work in PCG is…

The evaluation of procedural content generation (PCG) systems for generating video game levels is a complex and contested topic. Ideally, the field would have access to robust, generalisable and widely accepted evaluation approaches that…

人机交互 · 计算机科学 2024-04-30 Oliver Withington , Michael Cook , Laurissa Tokarchuk

Procedural content generation (PCG) can be applied to a wide variety of tasks in games, from narratives, levels and sounds, to trees and weapons. A large amount of game content is comprised of graphical assets, such as clouds, buildings or…

图形学 · 计算机科学 2025-06-30 Kaisei Fukaya , Damon Daylamani-Zad , Harry Agius

The past decade has seen a rapid increase in the level of research interest in procedural content generation (PCG) for digital games, and there are now numerous research avenues focused on new approaches for driving and applying PCG…

人机交互 · 计算机科学 2022-10-06 Oliver Withington , Laurissa Tokarchuk

Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based methods have been applied to various content types such as…

人工智能 · 计算机科学 2020-10-12 Jialin Liu , Sam Snodgrass , Ahmed Khalifa , Sebastian Risi , Georgios N. Yannakakis , Julian Togelius

This study presents an exploratory evaluation of Music Generation Systems (MGS) within contemporary music production workflows by examining eight open-source systems. The evaluation framework combines technical insights with practical…

音频与语音处理 · 电气工程与系统科学 2025-07-03 Shayan Dadman , Bernt Arild Bremdal , Andreas Bergsland

Procedural Content Generation (PCG) is the algorithmic generation of content, often applied to games. PCG and PCG via Machine Learning (PCGML) have appeared in published games. However, it can prove difficult to apply these approaches in…

人工智能 · 计算机科学 2023-09-26 Emily Halina , Matthew Guzdial

The generation of music that adapts dynamically to content and actions has an important role in building more immersive, memorable and emotive game experiences. To date, the development of adaptive music systems for video games is limited…

多媒体 · 计算机科学 2019-07-03 Patrick Hutchings , Jon McCormack

This paper presents a new approach to algorithmic composition, called predictive controlled music (PCM), which combines model predictive control (MPC) with music generation. PCM uses dynamic models to predict and optimize the music…

声音 · 计算机科学 2026-01-09 Midhun T. Augustine

Procedural content generation via Machine Learning (PCGML) is the umbrella term for approaches that generate content for games via machine learning. One of the benefits of PCGML is that, unlike search or grammar-based PCG, it does not…

人工智能 · 计算机科学 2018-09-26 Matthew Guzdial , Joshua Reno , Jonathan Chen , Gillian Smith , Mark Riedl

Procedural content generation (PCG) has recently become one of the hottest topics in computational intelligence and AI game researches. Among a variety of PCG techniques, search-based approaches overwhelmingly dominate PCG development at…

人工智能 · 计算机科学 2013-10-10 Jonathan Roberts , Ke Chen

Multi-modal music generation, using multiple modalities like text, images, and video alongside musical scores and audio as guidance, is an emerging research area with broad applications. This paper reviews this field, categorizing music…

声音 · 计算机科学 2026-03-09 Shuyu Li , Shulei Ji , Zihao Wang , Songruoyao Wu , Jiaxing Yu , Kejun Zhang

The utilization of deep learning techniques in generating various contents (such as image, text, etc.) has become a trend. Especially music, the topic of this paper, has attracted widespread attention of countless researchers.The whole…

声音 · 计算机科学 2020-11-16 Shulei Ji , Jing Luo , Xinyu Yang

Video game music (VGM) is often studied under the same lens as film music, which largely focuses on its theoretical functionality with relation to the identified genres of the media. However, till date, we are unaware of any systematic…

声音 · 计算机科学 2026-01-07 Daeun Hwang , Xuyuan Cai , Edward F. Melcer , Elin Carstensdottir

The term Procedural Content Generation (PCG) refers to the (semi-)automatic generation of game content by algorithmic means, and its methods are becoming increasingly popular in game-oriented research and industry. A special class of these…

人工智能 · 计算机科学 2023-02-17 Vanessa Volz , Boris Naujoks , Pascal Kerschke , Tea Tusar

In recent years, artificial intelligence (AI) has made significant progress in the field of music generation, driving innovation in music creation and applications. This paper provides a systematic review of the latest research advancements…

声音 · 计算机科学 2024-09-06 Yanxu Chen , Linshu Huang , Tian Gou

We introduce the concept of Procedural Content Generation via Knowledge Transformation (PCG-KT), a new lens and framework for characterizing PCG methods and approaches in which content generation is enabled by the process of knowledge…

人工智能 · 计算机科学 2023-05-02 Anurag Sarkar , Matthew Guzdial , Sam Snodgrass , Adam Summerville , Tiago Machado , Gillian Smith
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